HYPERION PROJECT

HYPERION is a research project of the European Union that focuses on the development of a decision support system for enhancing resilience and sustainable reconstruction of historic areas to cope with climate change and extreme eventsbased on novel sensors and advanced modeling tools.

The HYPERION goals are:

  • Reliable quantification of climatic, hydrological and atmospheric stressors using numerical quality modeling results evaluated for selected CC scenarios in the historical areas considered, covering processes and interactions from the short term to the long term (10-60 years).
  • Multi-hazard modeling encompassing single, contemporaneous (e.g., temperature extremes, humidity, wind, atmospheric pollutants) and cascading (mudslide/landslide following rainfall, etc.) hazards. Deterioration patterns and dose-response functions of building materials will be integrated into heat, air and moisture (HAM) simulations.
  • Analysis of construction materials and deterioration processes.
  • Implementation of a Hygro-Thermal (HT) simulation tool that considers the coupled phenomena of HAM transport through the elements of the structure under specific scenarios.
  • Implementation of a Hygro-Thermal (HT) simulation tool that considers the coupled phenomena of HAM transport through the elements of the structure under specific scenarios.
  • Environmental and material monitoring, including state identification and damage diagnosis: novel computer vision (CV) and machine learning (ML) algorithms will be implemented to exploit sensors, such as visible spectrum cameras, hyper/multispectral cameras, thermal/infrared/Ultra-Violet sensors, in order to obtain accurate inspection of CH sites.
  • Design of a holistic resilience assessment platform (HRAP) and decision support system (DSS) to enable community participation.
  • Integration, demonstration and on-site validation of the HYPERION platform through case studies in Greece, Italy, Norway and Spain.

HYPERION is conducting extensive testing at four demonstration sites, in Greece (Rhodes), Spain (Granada), Norway (Tønsberg) and Italy (Venice). The historic areas will be modeled at the building level using reduced order models based on archetype structures for each area. Several selected structures (CH value) will be modeled and monitored in detail. The demonstration will confirm the suitability of the HYPERION platform for multi-risk assessment and optimized operational and strategic decision making for the management and maintenance of historic areas, taking into account also other risks relevant to other sections of the city.

Our partner and researcher at the Higher Technical School of Civil Engineering of the University of Granada, Emilio Molero Melgarejo has contributed to the project by generating a database on exposure of buildings and infrastructures that are necessary for the risk and resilience assessment of the 4 pilot cities mentioned above..

The age of the building and its height have been two of the most important variables to take into account. For this purpose, the integration of LiDAR technology and Cadastre databases have been decisive:

HYPERION is a research project of the European Union that focuses on the development of a decision support system for enhancing resilience and sustainable reconstruction of historic areas to cope with climate change and extreme eventsbased on novel sensors and advanced modeling tools.

The HYPERION goals are:

  • Reliable quantification of climatic, hydrological and atmospheric stressors using numerical quality modeling results evaluated for selected CC scenarios in the historical areas considered, covering processes and interactions from the short term to the long term (10-60 years).
  • Multi-hazard modeling encompassing single, contemporaneous (e.g., temperature extremes, humidity, wind, atmospheric pollutants) and cascading (mudslide/landslide following rainfall, etc.) hazards. Deterioration patterns and dose-response functions of building materials will be integrated into heat, air and moisture (HAM) simulations.
  • Analysis of construction materials and deterioration processes.
  • Implementation of a Hygro-Thermal (HT) simulation tool that considers the coupled phenomena of HAM transport through the elements of the structure under specific scenarios.
  • Implementation of a Hygro-Thermal (HT) simulation tool that considers the coupled phenomena of HAM transport through the elements of the structure under specific scenarios.
  • Environmental and material monitoring, including state identification and damage diagnosis: novel computer vision (CV) and machine learning (ML) algorithms will be implemented to exploit sensors, such as visible spectrum cameras, hyper/multispectral cameras, thermal/infrared/Ultra-Violet sensors, in order to obtain accurate inspection of CH sites.
  • Design of a holistic resilience assessment platform (HRAP) and decision support system (DSS) to enable community participation.
  • Integration, demonstration and on-site validation of the HYPERION platform through case studies in Greece, Italy, Norway and Spain.

HYPERION is conducting extensive testing at four demonstration sites, in Greece (Rhodes), Spain (Granada), Norway (Tønsberg) and Italy (Venice). The historic areas will be modeled at the building level using reduced order models based on archetype structures for each area. Several selected structures (CH value) will be modeled and monitored in detail. The demonstration will confirm the suitability of the HYPERION platform for multi-risk assessment and optimized operational and strategic decision making for the management and maintenance of historic areas, taking into account also other risks relevant to other sections of the city.

Our partner and researcher at the Higher Technical School of Civil Engineering of the University of Granada, Emilio Molero Melgarejo has contributed to the project by generating a database on exposure of buildings and infrastructures that are necessary for the risk and resilience assessment of the 4 pilot cities mentioned above..

The age of the building and its height have been two of the most important variables to take into account. For this purpose, the integration of LiDAR technology and Cadastre databases have been decisive:

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